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The financial sector has been an early adopter of AI. It is likely that the use of algorithms in trading and the fact that most large financial firms already have teams of software developers aided the transition into data science and AI applications in the industry.

Large volumes of data, managed properly, are a boon for many industries, including the military. It would not be possible to mount effective military operations without knowing the when, where, and what in deploying resources. Military big data, therefore, helps defense leaders make better decisions, provided it is not “dark data.”

Machine vision has numerous use cases within the healthcare industry, including clinical solutions such as medical imaging and medical diagnostics. There are also possibilities in white collar automation such as medical transcription, which was one of the main interview topics in our white collar automation interview with the Executive Chairman of CognitiveScale.

In this second installment of the "Pitfalls to AI Adoption in the Enterprise" series, we're going to talk about underestimating the integration needs of artificial intelligence and machine learning.

The Institute of Electrical and Electronics Engineers (IEEE) comprises about 421,000 members in over 160 countries, and is known to most in the tech community for its publications, technology standards, conferences, and professional and educational activities. The organization has been developing internationally recognized technology standards for decades.

In this episode of the AI in Industry podcast, we speak with Marshall Choy, VP of Product at SambaNova, an AI hardware firm based in the Bay Area. SambaNova was founded by a number of Oracle and Sun Micro Systems alumni. We speak with Choy on two fundamental questions:

AI applications for the banking and finance industry include various software offerings for fraud detection and business intelligence. There are also predictive analytics applications outside of these that help banks automate financial processes and services that they offer their customers and provide internal analytics.

The Federal Bureau of Investigation has figured in many works of fiction as well as documentaries because what they do fascinates people. The representations have not always been favorable, but most people agree they have spearheaded many advances in science and technology in law enforcement.

Predictive and prescriptive analytics seem to be the most common types of AI applications at the top medical device companies. These companies, particularly Becton Dickinson, Medtronic, and Fresenius Medical Care, tend to partner with AI firms and vendors to create software that they intend to sell to hospitals most often.

What's harder than training an algorithm to detect images or automate a process? Collecting and cleaning the data in the first place.